1. Field of the Invention
The present invention relates to a method for providing U-Health service by using a specialized database, and more particularly to a method for providing U-Health service by using a database based on semantics and probabilistic inference.
2. Description of the Related Art
The Bayesian network (BN) is one of known methods for probabilistic information representation and inference, that have been widely used for diagnosis of diseases and other aliments in the Bio-information field. Through the use of the Bayesian network, it is possible to represent probabilistic information required for constructing a U-Health service. However, in order to construct a Bayesian network for diagnosing a specific disease, a specialist in a corresponding field must collect and analyze related information one by one, personally construct numerous Bayesian network nodes according to information elements related to the specific disease, and establish links between the information elements. Therefore, constructing such a Bayesian network requires a great deal of labor.
Meanwhile, recently, in order to overcome a limitation in a conventional text-based information representation methods, methods of managing various data based on ontologies have been widely researched and used. However, the existing ontologies represent fixed relationships between text-based information elements. That is, the existing ontologies are represented only with “having a connection” or “having no connection.”
When such text-based ontologies are applied to the Bayesian network as they are, concepts having no particular linguistic similarity to each other, for example, obesity and hypertension, are determined to have little connection with each other. However, since obesity exerts a great effect on hypertension induction, it may be inferred that the two concepts are closely connected with each other so that reliable U-Health service can be provided. Therefore, in order to construct a Bayesian network to provide reliable U-Health service, a method for reliably inferring a relationship between diseases is required.
Also, most conventional methods are implemented in such a manner as to simply convert all ontology classes to Bayesian network nodes. When a Bayesian network is created based on ontologies in which a great amount of information has been accumulated, the created Bayesian network becomes huge in scale, and becomes overly complicated. Especially, when ontology classes are applied to a Bayesian network in order to provide U-Health service, and a disease is deduced by using the Bayesian network, too many operations and a long time are required to analyze data. Therefore, it is necessary to develop a method for constructing a Bayesian network by extracting only ontologies relating to a specific disease, and providing U-Health service by using the Bayesian network.